ArticleMikrochimica acta2023
A promising and highly sensitive electrochemical platform for the detection of fentanyl and alfentanil in human serum.
Article in Mikrochimica acta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 12 citations in OpenAlex.
- Interpol review of forensic drug chemistry, 2022-2025.Forensic science international. Synergy · 2026Review
- Dual-Atom Catalyst Au@S-rGO for Rapid and Highly Sensitive Electrochemical Detection of Fentanyl in Serum.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- How new nanotechnologies are changing the opioid analysis scenery? A comparison with classical analytical methods.Forensic sciences research · 2024Review
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Authors and funding
9 authors at 2 institutions in 1 country.
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Abstract
A novel electrochemical method has been developed, based on a covalent organic framework (COF) and reduced graphene oxide (rGO), to detect fentanyl and alfentanil. COF nanomaterials with chrysanthemum morphology obtained by solvothermal reaction contain rich active sites for electrochemical catalytic reaction, thus improving the detection performance of the designed sensor. Reduced graphene oxide improves the sensor's sensitivity due to enhanced electron transfer. Under optimized experimental conditions, the fabricated electrode presents a linear range of 0.02 to 7.26 μM for alfentanil and 0.1 to 6.54 μM for fentanyl, with detection limits of 6.7 nM and 33 nM, respectively. In addition, the sensor possesses excellent selectivity, outstanding reproducibility, and acceptable stability. The proposed sensor is feasible for the reliable monitoring of fentanyl and alfentanil in human serum samples, with acceptable reliability and high potential in real-world applications. Finally, the electrochemical characteristic fingerprint of fentanyl is investigated by studying the electrochemical behavior of alfentanil and fentanyl on the electrode surface.
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Registered trials
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